scholarly journals Source Model of the 2014 Mw 6.9 Yutian Earthquake at the Southwestern End of the Altyn Tagh Fault in Tibet Estimated from Satellite Images

2020 ◽  
Vol 91 (6) ◽  
pp. 3161-3170
Author(s):  
Xing Li ◽  
Wenbin Xu ◽  
Sigurjón Jónsson ◽  
Yann Klinger ◽  
Guohong Zhang
Keyword(s):  
Ground Deformation ◽  
Source Parameters ◽  
Source Model ◽  
Coseismic Slip ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Altyn Tagh ◽  
Coulomb Failure Stress Change ◽  
Coulomb Failure ◽  
Source Geometry

Abstract Multiple fault segments ruptured during the 2014 Yutian earthquake, but the detailed source parameters and the mechanism of rupture complexity remain poorly understood. Here, we use high-resolution TanDEM-X satellite data and Satellite Pour l’Observation de la Terre-6/7 images to map the coseismic ground deformation field of the event. We find that the majority of coseismic slip occurred in the upper 10 km with the maximum left-lateral fault slip of ∼2.5  m at ∼6  km depth. The fault ruptured across a large 4.5 km extensional stepover from one left-lateral fault segment to another, with some right-lateral relay faulting in between. We find that the earthquake was followed by shallow afterslip concentrating at the southwestern end of coseismic rupture, in an area of many aftershocks and positive Coulomb failure stress change. Our findings demonstrate the power of satellite remote sensing technology in constraining source geometry and slip model of complex earthquakes when ground measurements are limited.

scholarly journals Bayesian Inversion of Wrapped Satellite Interferometric Phase to Estimate Fault and Volcano Surface Ground Deformation Models

2020 ◽  
Author(s):  
Yu Jiang ◽  
Pablo González
Keyword(s):  
Bayesian Approach ◽  
Ground Deformation ◽  
Source Parameters ◽  
Source Model ◽  
Phase Unwrapping ◽  
Point Of View ◽  
Model Parameters ◽  
Novel Approach ◽  
Ill Posed ◽  
The Impact

<p>Phase unwrapping is the process of recovering the absolute phase from unambiguous wrapped phase values that are measured modulo 2pi rad. From a mathematical point of view, phase unwrapping is an inverse problem, however, it is ill-posed and notoriously difficult to solve in the presence of noise. Meanwhile, phase unwrapping errors severely impact the estimation of earthquake and volcano source parameters using interferometric observations, therefore avoiding phase unwrapping completely is desirable. </p><p>A potential solution to avoid the unwrapping error issue completely, is to carry out a geophysical inversion directly on the wrapped phase observations. To overcome the need for phase unwrapping, we propose a novel approach that we can invert directly the interferometric wrapped phase, circumventing the ill-posed phase unwrapping processing step. This approach includes (1) a downsampling algorithm, (2) a method to estimate the covariance function of the wrapped phase, (3) an appropriate misfit function between the observed and the simulated wrapped phase. We also assess the uncertainties of source parameters within a Bayesian approach, and finally we test the robustness of the inversion methodology in multiple simulations including variable decorrelation and atmospheric noise simulations.</p><p>We demonstrate the proposed methodology on synthetic cases with variable noise and one real earthquake case. We show that the method is robust in challenging noise scenarios. We also show an improvement with the Bayesian approach in performance with respect to similar previous methods, resulting in avoiding any influence of seed starting models, and escaping local minima. We study the impact of a small percentage of incorrectly unwrapped phase observations in current state-of-the-art methods, and show that the presence of a small fraction of unwrapping errors affect strongly the estimation process. We conclude that in the cases where phase unwrapping is difficult or even impossible, the proposed inversion methodology with wrapped phase will provide an alternative approach to assess earthquake and volcano source model parameters.</p>

scholarly journals 3D Coseismic Deformation Field and Source Parameters of the 2017 Iran-Iraq Mw7.3 Earthquake Inferred from DInSAR and MAI Measurements

2019 ◽  
Vol 11 (19) ◽  
pp. 2248 ◽  
Author(s):  
Zhiheng Wang ◽  
Rui Zhang ◽  
Yuxin Liu
Keyword(s):  
Ground Deformation ◽  
Source Parameters ◽  
Field Measurements ◽  
Parameters Estimation ◽  
Deformation Field ◽  
Coseismic Deformation ◽  
United States Geological Survey ◽  
Data Sets ◽  
Coseismic Slip ◽  
Main Fault

The coseismic slip on the main fault related to the 2017 Iran-Iraq Mw7.3 earthquake has been investigated by previous studies using DInSAR (differential interferometric synthetic aperture radar) ground deformation measurements. However, DInSAR observation is not sensitive to the ground deformation in the along-track (AT) direction. Therefore, only the one-dimensional (1D) DInSAR coseismic deformation field measurements, derived in the LOS (line-of-sight) direction of radar, was applied in source parameters estimation. To further improve the accuracy of the fault slip inversion, the 3D (three-dimensional) coseismic deformation fields were reconstructed in the first place, by a combined use of the DInSAR and MAI (multiple aperture InSAR) measurements. Subsequently, the LOS and 3D deformation data sets were used as the constraint respectively, to perform a two-step inversion scheme to find an optimal geometry and slip distribution on the main fault. The comparative analysis indicated that the 3D coseismic deformation data sets improved the inversion-accuracy by 30%. Besides, the fault invention results revealed a deep dislocation on a NNW trending fault (the strike is 352.63°) extending about 60 km, along the fault dips 14.76° to the ENE. The estimated seismic moment is 8.44 × 1019 Nm (Mw7.3), which is close to the solution provided by USGS (United States Geological Survey). The slip distributed at the depth between 12 and 18 km, and the peak slip of 6.53 m appears at the depth of 14.5 km left near the epicenter. Considering the geological structure in the earthquake region and fault source-parameters, it comes to a preliminary conclusion that the ZMFF (the Zagros Mountain Front fault) should be responsible for the earthquake. In general, this paper demonstrated the superiority of using the 3D coseismic deformation fields on source parameters estimation.

Hyperspectral Remote Sensing Technology (HRST) program

1997 ◽  
Author(s):  
Tom Wilson ◽  
Rebecca Baugh ◽  
Ron Contillo ◽  
Tom Wilson ◽  
Rebecca Baugh ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Hyperspectral Remote Sensing ◽  
Remote Sensing Technology ◽  
Sensing Technology

Application of remote sensing technology to the relation of submarine pipelines and coastal morphology

1995 ◽  
Vol 32 (2) ◽  
pp. 77-83
Author(s):  
Y. Yüksel ◽  
D. Maktav ◽  
S. Kapdasli
Keyword(s):  
Remote Sensing ◽  
Sediment Transport ◽  
Surf Zone ◽  
Hydrodynamic Forces ◽  
Construction Site ◽  
Coastal Morphology ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Sea Bed

Submarine pipelines must be designed to resist wave and current induced hydrodynamic forces especially in and near the surf zone. They are buried as protection against forces in the surf zone, however this procedure is not always feasible particularly on a movable sea bed. For this reason the characteristics of the sediment transport on the construction site of beaches should be investigated. In this investigation, the application of the remote sensing method is introduced in order to determine and observe the coastal morphology, so that submarine pipelines may be protected against undesirable seabed movement.

scholarly journals Fault source investigation of the 6 December 2016 MwMw 6.5 Pidie Jaya, Indonesia, earthquake based on GPS and its implications of the geological survey result

2020 ◽  
Vol 14 (4) ◽  
pp. 405-412
Author(s):  
Endra Gunawan ◽  
Takuya Nishimura ◽  
Susilo Susilo ◽  
Sri Widiyantoro ◽  
Nanang T. Puspito ◽  
...  
Keyword(s):  
Surface Deformation ◽  
Source Parameters ◽  
Secondary Effects ◽  
Near Surface ◽  
Morphological Attributes ◽  
Ground Shaking ◽  
The North ◽  
Coulomb Failure ◽  
North And South ◽  
Fault Source

AbstractOn 6 December 2016 at 22:03 UTC, a devastating magnitude 6-class strike-slip earthquake occurred along an unidentified and unmapped fault in Pidie Jaya, northern Sumatra. We analysed the possible fault using continuous Global Positioning System (GPS) observation available in the region. In our investigation, we searched for the fault source parameters of the north- and south-dipping left-lateral faults and the west- and east-dipping right-lateral faults. We identified that the fault responsible for the earthquake was located offshore, with a southwest-northeast direction. We also computed the Coulomb failure stress and compared the result with the distribution of the aftershocks. In this study, we demonstrated that the result of the geological field survey conducted soon after the mainshock was attributed to the secondary effects of ground shaking and near-surface deformation, and not surface faulting. The newly identified offshore fault proposed by this study calls for further investigation of the corresponding submarine morphological attributes in this particular region.

Based on IDRISI Remote Sensing Images Land-Use Types of Supervised Classification Techniques

2013 ◽  
Vol 415 ◽  
pp. 305-308
Author(s):  
Kun Zhang ◽  
Hai Feng Wang ◽  
Zhuang Li
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Classification Techniques ◽  
Analysis And Evaluation ◽  
Remote Sensing Classification ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Remote Sensing Image Classification ◽  
Land Use Types ◽  
Area Distribution

With remote sensing technology and computer technology, remote sensing classification technology has been rapid progress. In the traditional classification of remote sensing technology, based on the combination of today's technology in the field of remote sensing image classification, some new developments and applications for land cover classification techniques to make more comprehensive elaboration. Using the minimum distance classifier extracts of the study area land use types. Ultimately extracted land use study area distribution image and make its analysis and evaluation.

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